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A genetic algorithm approach for modelling low voltage network demands

Abstract:

Distribution network operators (DNOs) are increasingly concerned about the impact of low carbon technologies on the low voltage (LV) networks. More advanced metering infrastructures provide numerous opportunities for more accurate load flow analysis of the LV networks. However, such data may not be readily available for DNOs and in any case is likely to be expensive. Modelling tools are required which can provide realistic, yet accurate, load profiles as input for a network modelling tool, wi...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.apenergy.2017.06.057

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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
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Grant:
New Thames Valley Vision Project (SSET203 New Thames Valley Vision
Publisher:
Elsevier Publisher's website
Journal:
Applied Energy Journal website
Volume:
203
Pages:
463-473
Publication date:
2017-06-23
Acceptance date:
2017-06-16
DOI:
ISSN:
0306-2619
Source identifiers:
667122
Keywords:
Pubs id:
pubs:667122
UUID:
uuid:6eba1ac0-e65c-4127-9999-ddfaaa863f7f
Local pid:
pubs:667122
Deposit date:
2017-06-19

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